self-evolving-single-agent

name	self-evolving-single-agent
description	Use when generating a single installable agent that should keep learning, track sources, refresh research, propose repairs, or improve itself over time without becoming a multi-agent team.

Self-Evolving Single Agent

Procedure

1. Keep the package as one worker unless the user asks for a team.
2. Run docs/builder-interview-research-gate.md before generation: ask an 8-12 question first batch, research official sources, similar agent repositories or comparables, academic/professional theory, and plugin docs, compare tool/plugin choices, and write the domain-expert synthesis plus prompt-performance contract before creating the worker prompt.
3. Add memory architecture even for the single worker:
   • .agentlas/memory-map.json;
   • .agentlas/vault-references.json;
   • project memory owned by PM Soul/project owner;
   • Memory Events and Memory Tickets for durable updates.
4. If the task depends on current sources, add a research-refresh command, watchlist memory section, references, and optional scheduled workflow.
5. Add docs/builder-interview.md, docs/research-sources.md, docs/tool-selection.md, docs/domain-expert-synthesis.md, docs/prompt-performance-contract.md, and .agentlas/capability-eval-plan.json unless explicitly creating a minimal private scaffold.
6. Make self-evolution proposal-first: draft patches or repair kits, then wait for human approval before changing tools, connectors, secrets, or core instructions.
7. Add .agentlas/global-commands.json and one public global command for the worker across Claude Code, Codex, Gemini CLI, generic AGENTS.md, and terminal adapters.

Output

Return agent_package, skills, memory_contract, refresh_loop, approval_gate, global_commands, and verification.